Ensemble Learning Based Classification of High Resolution SAR Images

dc.contributor.authorTurkmenli, Ilter
dc.contributor.authorKayabol, Koray
dc.date.accessioned2025-10-29T11:34:42Z
dc.date.issued2019
dc.departmentFakülteler, Mühendislik Fakültesi, Elektronik Mühendisliği Bölümü
dc.description27th Signal Processing and Communications Applications Conference (SIU) -- APR 24-26, 2019 -- Sivas Cumhuriyet Univ, Sivas, TURKEY
dc.description.abstractThe improvements in SAR systems having a very wide range of applications lead to obtain higher resolution images and consequently to increase the need for classification of these images. In this paper, approximate sparse multinomial logistic regression (ASMLR) based bagging method as a ensemble learning method is proposed for classification of SAR images. Based on the classification of real SAR images, it is shown that obtained better classification results with proposed method compared to widely used classifiers.
dc.description.sponsorshipIEEE Turkey Sect,Turkcell,Turkhavacilik Uzaysanayii,Turitak Bilgem,Gebze Teknik Univ,SAP, Detaysoft,NETAS,Havelsan
dc.identifier.isbn978-1-7281-1904-5
dc.identifier.issn2165-0608
dc.identifier.scopus2-s2.0-85071979617
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://hdl.handle.net/20.500.14854/13006
dc.identifier.wosWOS:000518994300028
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isotr
dc.publisherIEEE
dc.relation.ispartof2019 27th Signal Processing and Communications Applications Conference (Siu)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20251020
dc.subjectSAR image
dc.subjectclassification
dc.subjectensamble learning
dc.subjectASMLR
dc.subjectbagging
dc.titleEnsemble Learning Based Classification of High Resolution SAR Images
dc.typeConference Object

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